Scientific overview: CSCI-CITAC Annual General Meeting and Young Investigator’s Forum 2013
Bibliographic record
Abstract
The 2013 joint Canadian Society of Clinician Investigators (CSCI)-Clinical Investigator Trainee Association of Canada/Association des cliniciens-chercheurs en formation du Canada (CITAC/ACCFC) annual general meeting(AGM) was held in Ottawa, September 2013. The symposium focused on "Applications of the 'omics' to Clinical Practice", with presentations from Drs. William T. Gibson (University of British Columbia), Julie Ho (University of Manitoba) and David Hwang (University of Toronto), discussing topics of genome, proteome and the microbiome, respectively. Other highlights from the 2013 AGM include presentations by Dr. Salim Yusuf (McMaster University, 2013 CSCI-RCPSC Henry Friesen Award winner), Dr. Gary Lewis (University of Toronto, 2013 CSCI Distinguished Scientist Award winner) and Dr. Michael Taylor (University of Toronto, 2013 Joe Doupe Award winner). The CSCI/CITAC/Friends of CIHR Joint Symposium consisted of presentations from Drs. John Bell (University of Ottawa), Dan Drucker (University of Toronto) and Heather J. Dean (University of Manitoba). Finally, the meeting ended with the presentation "The Power of an Idea to Bring Ideas to Power" by Dr. Harvey V. Fineberg (President, U.S. Institute of Medicine), the winner of the 2013 Henry Friesen International Prize. Also presented at the conference was research by clinician investigator (CI) trainees from across Canada; ie., those enrolled in MD/MSc, MD/PhD or Clinician Investigator Program(CIP) programs. Canadian trainees' research extended beyond the pillar of biomedical research, covering the spectrum between basic and clinical research, with a focus on the causes of significant morbidity and mortality for Canadians, including cancers, infectious diseases and other maladies. It is this research that we have summarized in this review.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.020 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.016 | 0.010 |
| Insufficient payload (model declined to judge) | 0.121 | 0.101 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".